{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "source": [
    "import numpy as np\n",
    "import torch\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "from os import name\n",
    "import argparse\n",
    "import os,sys\n"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "sys.path.insert(0, '../')\n",
    "from src.utils import read_txt_embeddings, normalize_embeddings, export_embeddings"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "params = argparse.Namespace()\n",
    "params.src_lang = 'zh'\n",
    "params.tgt_lang = 'en'\n",
    "params.src_emb = '../data/wiki.zh.vec'\n",
    "params.tgt_emb = '../data/wiki.en.vec'\n",
    "params.emb_dim = 300\n",
    "params.max_vocab = 200000\n",
    "params.cuda = True\n",
    "params.export = \"txt\"\n",
    "params.exp_path = \"../dumped/tmp_itrecent_wordvec\"\n",
    "\n",
    "params.src_dico, src_emb = read_txt_embeddings(params, True, False)\n",
    "params.tgt_dico, tgt_emb = read_txt_embeddings(params, False, False)\n"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "data = pd.DataFrame(data=torch.stack([src_emb.norm(dim=1), tgt_emb.norm(dim=1)]).T.cpu().numpy(), index=range(params.max_vocab), columns=['X', 'Y'])"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "source": [
    "sns.scatterplot(\n",
    "                palette=\"ch:r=-.2,d=.3_r\",\n",
    "                sizes=(1, 20), linewidth=0,\n",
    "                data=data)"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "metadata": {},
     "execution_count": 12
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "source": [
    "f, ax = plt.subplots(figsize=(6.5, 6.5))\n",
    "sns.scatterplot(\n",
    "                palette=\"ch:r=-.2,d=.3_r\",\n",
    "                sizes=(1, 20), linewidth=0,\n",
    "                data=data['X'], ax=ax)\n",
    "f, ax = plt.subplots(figsize=(6.5, 6.5))\n",
    "sns.scatterplot(\n",
    "                palette=\"ch:r=-.2,d=.3_r\",\n",
    "                sizes=(1, 20), linewidth=0,\n",
    "                data=data['Y'], ax=ax)"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Y'>"
      ]
     },
     "metadata": {},
     "execution_count": 15
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 468x468 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 468x468 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "source": [
    "data.loc[data['X']>20]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>38.152245</td>\n",
       "      <td>2.052650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>663</th>\n",
       "      <td>34.361263</td>\n",
       "      <td>3.048134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13638</th>\n",
       "      <td>24.292395</td>\n",
       "      <td>4.889937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26175</th>\n",
       "      <td>498.418823</td>\n",
       "      <td>4.649265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34311</th>\n",
       "      <td>21.584545</td>\n",
       "      <td>7.910657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61529</th>\n",
       "      <td>47.023296</td>\n",
       "      <td>4.503255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66183</th>\n",
       "      <td>33.266071</td>\n",
       "      <td>4.829961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94803</th>\n",
       "      <td>53.008812</td>\n",
       "      <td>8.946668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95332</th>\n",
       "      <td>29.809576</td>\n",
       "      <td>5.431878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106686</th>\n",
       "      <td>124.756119</td>\n",
       "      <td>3.828399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181583</th>\n",
       "      <td>57.582066</td>\n",
       "      <td>4.762142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198821</th>\n",
       "      <td>38.852947</td>\n",
       "      <td>6.415579</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 X         Y\n",
       "0        38.152245  2.052650\n",
       "663      34.361263  3.048134\n",
       "13638    24.292395  4.889937\n",
       "26175   498.418823  4.649265\n",
       "34311    21.584545  7.910657\n",
       "61529    47.023296  4.503255\n",
       "66183    33.266071  4.829961\n",
       "94803    53.008812  8.946668\n",
       "95332    29.809576  5.431878\n",
       "106686  124.756119  3.828399\n",
       "181583   57.582066  4.762142\n",
       "198821   38.852947  6.415579"
      ]
     },
     "metadata": {},
     "execution_count": 32
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "source": [
    "params.src_dico[34311]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "'і'"
      ]
     },
     "metadata": {},
     "execution_count": 37
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  }
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